BACKGROUND Synovitis,acne,pustulosis,hyperostosis,and osteitis(SAPHO)syndrome,a rare inflammatory disease,was described in 1987 by Chamot et al,who identified its common characteristics and transitional forms through ...BACKGROUND Synovitis,acne,pustulosis,hyperostosis,and osteitis(SAPHO)syndrome,a rare inflammatory disease,was described in 1987 by Chamot et al,who identified its common characteristics and transitional forms through case reports.The inci-dence rate is now 1 in 10000 among Caucasians and 0.00144 in 10000 among Japanese.Pneumothorax occurs when gas enters the pleural cavity,typically due to lung disease or chest trauma,and is characterized as either spontaneous or traumatic.Spontaneous pneumothorax is commonly linked to congenital lung tissue abnormalities or lung conditions,such as ruptured pulmonary bullae,emphysema,and bronchial asthma.Respiratory involvement in SAPHO syn-drome has historically been noted.CASE SUMMARY We present the case of a 44-year-old male patient who had previously been diagnosed with SAPHO syndrome.Following a two-year cessation of methotrexate therapy,he experienced recurrent anterior chest wall and joint pain accompanied by dyspnea.We conducted a comprehensive examination for the patient,which included physical examination,laboratory tests,and imaging studies.The clinical presentation and treatment outcomes suggest that his pneumothorax was related to an episode of SAPHO syndrome.We performed closed thoracic drainage surgery for the patient and treated his symptoms with etoricoxib(60 mg daily).Upon discharge,methotrexate was prescribed again.In subsequent follow-ups,there was no recurrence of joint and respiratory symptoms observed in the patient.CONCLUSION SAPHO syndrome has been proposed as a transitional stage between ankylosing spondylitis and psoriatic arthritis.One study reported a 0.29%incidence of spontaneous pneumothorax in patients with ankylosing spondylitis,higher than in the general population.Additionally,30%of patients with SAPHO syndrome test positive for HLA-B27,an antigen linked to ankylosing spondylitis.Symptomatically,some patients with SAPHO syndrome meet diagnostic criteria for ankylosing spondylitis,with sternoclavicular joint involvement and paravertebral ossific-ations resembling syndesmophytes in ankylosing spondylitis.These features suggest a possible linked between SAPHO syndrome and ankylosing spondylitis.展开更多
Atomically precise palladium(Pd)clusters are emerging as versatile nanomaterials with applications in catalysis and biomedicine.This study explores the synthesis,structure evolution,and catalytic properties of Pd clus...Atomically precise palladium(Pd)clusters are emerging as versatile nanomaterials with applications in catalysis and biomedicine.This study explores the synthesis,structure evolution,and catalytic properties of Pd clusters stabilized by cyclohexanethiol(HSC_(6)H_(11))ligands.Using electrospray ionization mass spectrometry(ESI-MS)and single-crystal X-ray diffraction(SXRD),structures of the Pd clusters ranging from Pd4(SC_(6)H_(11))8 to Pd18(SC_(6)H_(11))36 were determined.This analysis revealed a structure evolution from polygonal to elliptical geometries of the PdnS2n frameworks as the cluster size increased.UV-Vis-NIR spectroscopy,combined with quantum chemical calculations,elucidated changes in the electronic structure of the clusters.Catalytic studies on the Sonogashira cross-coupling reactions demonstrated a size-dependent decline in activity attributed to variations in structural arrangements and electronic properties.Mechanistic insights proposed a distinctive Pd(Ⅱ)-Pd(Ⅳ)catalytic cycle.This research underscores how ligands and cluster size influence the structures and properties of Pd clusters,offering valuable insights for the future design and application of Pd clusters in advanced catalysis and beyond.展开更多
Charge-transfer(CT)stoichiometric cocrystals are promising choice of organic materials for unveiling the structure-property relationship.However,due to the contradiction between large CT degree required for strong NIR...Charge-transfer(CT)stoichiometric cocrystals are promising choice of organic materials for unveiling the structure-property relationship.However,due to the contradiction between large CT degree required for strong NIR absorption and flexible molecular stacking,construction of stoichiomorphism-based cocystals with near-infrared(NIR)photothermal property remains challenging.Herein,the first example of stoichiomorphism-based photothermal cocrystals were accomplished through the adaptive assembly of 3,3,5,5-tetramethylbenzidine(TMB)donor and 1,2,4,5-tetracyanobenzene(TCNB)acceptor.The selective cocrystallization could be controlled by varying the donor-acceptor stoichiometries via a surfactantassisted method,resulting in two cocrystals with 1:1(T1C1)and 1:2(T2C1)stoichiometries.The absorbance intensity of T1C1 at 808 nm was nearly twice that of T2C1,while the photothermal conversion efficiency(PCE)of the former was 60.3%±0.6%,approximately 80%of that for the latter(75.5%±2.6%),which might be caused by the different intermolecular interactions in distinct molecular stacking patterns.Notably,both excellent PCEs of stoichiometric cocrystals were attributed to the nonradiative transition process,including internal conversion and charge dissociation processes,as elucidated by femtosecond transient absorption spectroscopy measurements.Furthermore,T1C1 was used as an NIR heater for preparing agarose-based photothermal hydrogel,showing great potential for light-controlled in-situ gelation.This strategy of balancing the CT degree and molecular packing orientation not only uncovered the relationship between stoichiometric stacking and photothermal property,but also provided an opportunity to develop advanced organic optoelectronic materials.展开更多
With the rapid development of human civilization,the concentration of CO_(2)in the atmosphere has sharply increased in the past century,resulting in global temperature anomaly,extreme climate events,and eco-environmen...With the rapid development of human civilization,the concentration of CO_(2)in the atmosphere has sharply increased in the past century,resulting in global temperature anomaly,extreme climate events,and eco-environmental disturbances.The green-house gas CO_(2)is mainly released from the process of fossil fuel utilization and combustion.展开更多
The poor electrode/electrolyte interface compatibility and inferior electrolyte oxidative tolerance in commercial ethylene carbonate(EC)-based electrolytes have hindered the development of high-voltage sodium-ion batt...The poor electrode/electrolyte interface compatibility and inferior electrolyte oxidative tolerance in commercial ethylene carbonate(EC)-based electrolytes have hindered the development of high-voltage sodium-ion batteries(SIBs).In this study,an anionic chemistry strategy is proposed to strengthen Na^(+)-anion coordination in the solvation sheath,and subsequently reduce the coordination numbers of EC solvents with the addition of NaClO_(4)into NaPF_(6)/EC/DEC electrolytes.Theoretical and experimental results confirm that the competitive coordination capabilities of Na^(+)-ClO_(4)^(-),with high binding energy,induce a wide electrochemical window up to 4.8 V,highly reversible Na^(+)plating/stripping,and fast desolvation kinetics at the electrode/electrolyte interface,thereby hindering the continuous electrolyte decomposition.The optimized electrolyte PEDCF-0.20 demonstrates weakened Na^(+)-EC coordination,increased interaction of Na^(+)-anion in solvation,facilitating the formation of an inorganic-rich interface layer.Consequently,a 2.1 A h cylindrical full cell of hard carbon//NaNi_(1/3)Fe_(1/3)Mn_(1/3)O_(2)delivers an impressive capacity retention of 93.7% after 300 cycles at an extended charging cutoff voltage of 4.1 V.This work provides a new insight into regulating the competitive coordination of anions to guarantee the remarkable cycling stability of high-voltage SIBs.展开更多
The fracture energy of fiber-reinforced concrete(FRC)affects the durability and structural performance of concrete elements.Advancements in experimental studies have yet to overcome the challenges of estimating fractu...The fracture energy of fiber-reinforced concrete(FRC)affects the durability and structural performance of concrete elements.Advancements in experimental studies have yet to overcome the challenges of estimating fracture energy,as the process remains time-intensive and costly.Therefore,machine learning techniques have emerged as powerful alternatives.This study aims to investigate the performance of machine learning techniques to predict the fracture energy of FRC.For this purpose,500 data points,including 8 input parameters that affect the fracture energy of FRC,are collected fromthree-point bending tests and employed to train and evaluate themachine learning techniques.The findings showed that Gaussian process regression(GPR)outperforms all other models in terms of predictive accuracy,achieving the highest R2 of 0.93 and the lowest RMSE of 13.91 during holdout cross-validation.It is then followed by support vector regression(SVR)and extreme gradient boosting regression(XGBR),whereas K-nearest neighbours(KNN)and random forest regression(RFR)show the weakest predictions.The superiority of GPR is further reinforced in a 5-fold cross-validation,where it consistently delivers an average R2 above 0.96 and ranks highest in overall predictive performance.Empirical testing with additional sample sets validates GPR’s model on the key mix parameter’s impact on fracture energy,cementing its claim.The Fly-Ash cement exhibits the greatest fracture energy due to superior fiber-matrix interaction,whereas the glass fiber dominates energy absorption amongst the other types of fibers.In addition,increasing the water-to-cement(W/C)ratio from 0.30 to 0.50 yields a significant improvement in fracture energy,which aligns well with the machine learning predictions.Similarly,loading rate positively correlates with fracture energy,highlighting the strain-rate sensitivity of FRC.This work is the missing link to integrate experimental fracture mechanics and computational intelligence,optimally and reasonably predicting and refining the fracture energy of FRC.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making pr...BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making precise treatment plans and improving patient prognosis.AIM To establish an intratumoral and peritumoral model for predicting ER in HCC patients following curative ablation.METHODS This study included a total of 288 patients from three Centers.The patients were divided into a primary cohort(n=222)and an external cohort(n=66).Radiomics and deep learning methods were combined for feature extraction,and models were constructed following a three-step feature selection process.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),while calibration curves and decision curve analysis(DCA)were used to assess calibration and clinical utility.Finally,Kaplan-Meier(K-M)analysis was used to stratify patients according to progression-free survival(PFS)and overall survival(OS).RESULTS The combined model,which utilizes the light gradient boosting machine learning algorithm and incorporates both intratumoral and peritumoral regions(5 mm and 10 mm),demonstrated the best predictive performance for ER following HCC ablation,achieving AUCs of 0.924 in the training set,0.899 in the internal validation set,and 0.839 in the external validation set.Calibration and DCA curves confirmed strong calibration and clinical utility,whereas K-M curves provided risk stratification for PFS and OS in HCC patients.CONCLUSION The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions.This model provides a noninvasive,effective,and reliable method for predicting ER after curative ablation of HCC.展开更多
Objective:To evaluate the antioxidant activity of aqueous extract of Atoringa oleifeta M.oleifera) young leaves by in vivo as well as in vitro assays.Methods:In vitro study included estimation of total phenolic,total ...Objective:To evaluate the antioxidant activity of aqueous extract of Atoringa oleifeta M.oleifera) young leaves by in vivo as well as in vitro assays.Methods:In vitro study included estimation of total phenolic,total ilavonol,total flavonoid and total antioxidant power(FRAP assay).Tn addition, in vivo study was done with the identified most effective dose of 200 nig/kg of its lyophilized powder on normal and diabetic rats.Its effect on different oxidative free radical scavenging enzymes,viz,superoxide dismutase(SOD),catalase(CAT),glutathione-S-transferase(GST),lipid peroxide(LPO) contents were measured.Results:Significant increase in activities of SOD.CAT, GST while,a decrease in LPO content was observed.Whereas,total phenolic,flavonoid and ilavonol contents in the extract were found to be 120 mg/g of CAK,40.5 mg/g of QEK and 12.12 mg/g of QE,respectively.On the other hand.FRAP assay results of M.oleifera leaves was(85.00±5.00)μM of Fe^+/g of extract powder.Conclusions:The significant antioxidant activities of M.oleifera leaves from both in vivo as well as in vitro studies suggests that the regular intake of its leaves through diet can protect normal as well as diabetic patients against oxidative damage.展开更多
The design of an antenna requires a careful selection of its parameters to retain the desired performance.However,this task is time-consuming when the traditional approaches are employed,which represents a significant...The design of an antenna requires a careful selection of its parameters to retain the desired performance.However,this task is time-consuming when the traditional approaches are employed,which represents a significant challenge.On the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended performance.In this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial antenna.The proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep network.This optimized network is used to retrieve the metamaterial bandwidth given a set of features.In addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.展开更多
Colorectal cancer(CRC)is among the leading causes of cancer mortality.The lifetime risk of developing CRC is about 5%in adult males and females.CRC is usually diagnosed at an advanced stage,and at this point therapy h...Colorectal cancer(CRC)is among the leading causes of cancer mortality.The lifetime risk of developing CRC is about 5%in adult males and females.CRC is usually diagnosed at an advanced stage,and at this point therapy has a limited impact on cure rates and long-term survival.Novel and/or improved CRC therapeutic options are needed.The involvement of microRNAs(miRNAs)in cancer development has been reported,and their regulation in many oncogenic pathways suggests their potent tumor suppressor action.Although miRNAs provide a promising therapeutic approach for cancer,challenges such as biodegradation,specificity,stability and toxicity,impede their progression into clinical trials.Nanotechnology strategies offer diverse advantages for the use of miRNAs for CRC-targeted delivery and therapy.The merits of using nanocarriers for targeted delivery of miRNA-formulations are presented herein to highlight the role they can play in miRNA-based CRC therapy by targeting different stages of the disease.展开更多
Tandem device architectures offer a route to greatly increase the maximum possible power conversion efficiencies(PCEs)of polymer solar cells,however,the complexity of tandem cell device fabrication(such as selecting b...Tandem device architectures offer a route to greatly increase the maximum possible power conversion efficiencies(PCEs)of polymer solar cells,however,the complexity of tandem cell device fabrication(such as selecting bandgaps of the front and back cells,current matching,thickness,and recombination layer optimization)often result in lower PCEs than are observed in single-junction devices.In this study,we analyze the influence of front cell and back cell bandgaps and use transfer matrix modeling to rationally design and optimize effective tandem solar cell structures before actual device fabrication.Our approach allows us to estimate tandem device parameters based on known absorption coefficients and open-circuit voltages of different active layer materials and design devices without wasting valuable time and materials.Using this approach,we have investigated a series of wide bandgap,high voltage photovoltaic polymers as front cells in tandem devices with PTB7-Th as a back cell.In this way,we have been able to demonstrate tandem devices with PCE of up to 12.8%with minimal consumption of valuable photoactive materials in tandem device optimization.This value represents one of the highest PCE values to date for fullerene-based tandem solar cells.展开更多
Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for...Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.展开更多
The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the d...The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.展开更多
Encapsulation and controlled release of volatile molecules such as fragrances in a designed manner is important but challenging for the flavor and fragrance industry.Here,we report the tuning release of volatile molec...Encapsulation and controlled release of volatile molecules such as fragrances in a designed manner is important but challenging for the flavor and fragrance industry.Here,we report the tuning release of volatile molecules by postsynthetic modification of an amine-terminated metal-organic framework(MOF)MIL-101-NH_(2).By amidation,we obtained three MIL-101 MOFs,the trimethylacetamideterminated TC-MIL-101,the benzamide-terminated BC-MIL-101,and the oxalic acid monoamideterminated OC-MIL-101.All the MOFs can efficiently encapsulate volatile molecules.Moreover,we demonstrate that the release profile of volatiles can be widely tuned to sustain the release in several days to months and even over a year using different modified MIL-101 MOFs.We show that the release profiles are correlated with the binding energies between the vip volatiles and pores in MOFs.The pore diffusion and the synergistic transport are the rate-limiting step of the vip molecules from the modified MOFs.展开更多
With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,w...With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,which demands for new solutions.Terahertz(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information network.THz communication has great application prospects in military-civilian integration and coordinated development.In China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the world.Therefore,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G.This paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel model.Then,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver.Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.展开更多
Inverted perovskite solar cells(PSCs)have attracted interest due to their simple fabrication,long-term stability,and small hysteresis[1-3].It is noteworthy that the quality of the hole-transport layer(HTL)largely dete...Inverted perovskite solar cells(PSCs)have attracted interest due to their simple fabrication,long-term stability,and small hysteresis[1-3].It is noteworthy that the quality of the hole-transport layer(HTL)largely determines the device performance.Nickel oxide(NiO_(x))has been paid great attention as a hole-transport material in PSCs because of its natural p-type property,low cost,good stability,and high transmittance[4,5].展开更多
Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)applications.The SA is utilized in various applications,namely,ed...Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)applications.The SA is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock market.Various researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the SA for multiple languages,for instance,English and Chinese.Due to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted SA for Hindi movie reviews.The current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLSA-MR)model.The presented IMDLSA-MR technique initially applies different levels of pre-processing to convert the input data into a compatible format.Besides,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed data.The Deep Belief Network(DBN)model is utilized to analyse and classify the sentiments.Finally,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the work.Different experimental analyses were conducted to validate the better performance of the proposed IMDLSA-MR model.The comparative study outcomes highlighted the enhanced performance of the proposed IMDLSA-MR model over recent DL models with a maximum accuracy of 98.92%.展开更多
The main objective of this study is to understand the runoff, sediment yield and water quality of the Upper Indus River Basin of Pakistan. To achieve this goal, specific objectives have been met which include, setup o...The main objective of this study is to understand the runoff, sediment yield and water quality of the Upper Indus River Basin of Pakistan. To achieve this goal, specific objectives have been met which include, setup of a hydrological model using Soil and Water Assessment Tool (SWAT) then calibration and validation of the hydrological model using river discharges and in the end investigating the performance of the hydrological model by SWAT. This research will have great impacts on socio-economic conditions of Pakistan because study of upper Indus River basin is imperative to provide data needed for its management, and to warrant that it is sustainable to support the increasing population and conservational flows. A set of programmable mapping components MapWindow Geographic Information System (GIS) was used which is an open source GIS based mapping application. It is SWAT used spatially distributed information on elevation, land use, slope and soil. The program Sequential Uncertainty Fitting ver.2 (SUFI-2) in a combination of uncertainty analysis and calibration of outputs was used in SWAT-CUP. SWAT model used input data, which have climate information to obtain results. The observed climate data of temperature gauges and rain gauge were used as input in the SWAT model;the calibration results for three discharge stations were produced. The initial P-factor value was satisfactory but more iteration to attempt narrow uncertainty band with improving goal function, resulted in small percentage of observed data within uncertainty band. A warm up period of three years (1979-1982) was used for simulation of SWAT model. The model was calibrated for selected three catchments for the period 1982-2000 and validated for period 2001-2010. Results are quite comparable with the observed flows.展开更多
Background:The Shexiang Baoxin Pill(MUSKARDIA)has been used for treating coronary artery disease(CAD)and angina for more than 30 years in China.Nevertheless,methodologically sound trials on the use of MUSKARDIA in CAD...Background:The Shexiang Baoxin Pill(MUSKARDIA)has been used for treating coronary artery disease(CAD)and angina for more than 30 years in China.Nevertheless,methodologically sound trials on the use of MUSKARDIA in CAD patients are scarce.The aim of the study is to determine the effects of MUSKARDIA as an add-on to optimal medical therapy(OMT)in patients with stable CAD.Methods:A total of 2674 participants with stable CAD from 97 hospitals in China were randomized 1:1 to a MUSKARDIA or placebo group for 24 months.Both groups received OMT according to local tertiary hospital protocols.The primary outcome was the occurrence of a major adverse cardiovascular event(MACE),defined as a composite of cardiovascular death,non-fatal myocardial infarction(MI),or non-fatal stroke.Secondary outcomes included all-cause mortality,non-fatal MI,non-fatal stroke,hospitalization for unstable angina or heart failure,peripheral revascularization,angina stability and angina frequency.Results:In all,99.7%of the patients were treated with aspirin and 93.0%with statin.After 2 years of treatment,the occurrence of MACEs was reduced by 26.9%in the MUSKARDIA group(MUSKARDIA:1.9%vs.placebo:2.6%;odds ratio=0.80;95%confidence interval:0.45-1.07;P=0.2869).Angina frequency was significantly reduced in the MUSKARDIA group at 18 months(P=0.0362).Other secondary endpoints were similar between the two groups.The rates of adverse events were also similar between the two groups(MUSKARDIA:17.7%vs.placebo:17.4%,P=0.8785).Conclusions:As an add-on to OMT,MUSKARDIA is safe and significantly reduces angina frequency in patients with stable CAD.Moreover,the use of MUSKARDIA is associated with a trend toward reduced MACEs in patients with stable CAD.The results suggest that MUSKARDIA can be used to manage patients with CAD.Trial registration:chictr.org.cn,No.ChiCTR-TRC-12003513.展开更多
To the Editor:Primary familial brain calcification (PFBC) is a rare genetically degenerative disease that is generally characterized by symmetrical,bilateral calcinosis in the basal ganglia,thalamus,dentate nuclei,and...To the Editor:Primary familial brain calcification (PFBC) is a rare genetically degenerative disease that is generally characterized by symmetrical,bilateral calcinosis in the basal ganglia,thalamus,dentate nuclei,and other brain regions and mainly manifests with neurological and psychiatric symptoms. A growing number of studies have reported associations between this condition and pathogenic mutations,such as those in the SLC2OA2,PDGFRB,PDGFB,XPR1,and MYORG genes, Few studies have evaluated familial clinical characteristics, such as the volume of basal ganglia calcification (VBGC), and the results of clinical tests to determine serum levels of calcium (Ca),magnesium (Mg),phosphorus (P),iron (Fe), aluminum (A1),arsenic (As),cobalt (Co),parathyroid hormone (PTH),and calcitonin (Ct),or the relationship between patient age and the VBGC in PFBC.展开更多
基金Supported by The National Natural Science Foundation of China,No.82074246.
文摘BACKGROUND Synovitis,acne,pustulosis,hyperostosis,and osteitis(SAPHO)syndrome,a rare inflammatory disease,was described in 1987 by Chamot et al,who identified its common characteristics and transitional forms through case reports.The inci-dence rate is now 1 in 10000 among Caucasians and 0.00144 in 10000 among Japanese.Pneumothorax occurs when gas enters the pleural cavity,typically due to lung disease or chest trauma,and is characterized as either spontaneous or traumatic.Spontaneous pneumothorax is commonly linked to congenital lung tissue abnormalities or lung conditions,such as ruptured pulmonary bullae,emphysema,and bronchial asthma.Respiratory involvement in SAPHO syn-drome has historically been noted.CASE SUMMARY We present the case of a 44-year-old male patient who had previously been diagnosed with SAPHO syndrome.Following a two-year cessation of methotrexate therapy,he experienced recurrent anterior chest wall and joint pain accompanied by dyspnea.We conducted a comprehensive examination for the patient,which included physical examination,laboratory tests,and imaging studies.The clinical presentation and treatment outcomes suggest that his pneumothorax was related to an episode of SAPHO syndrome.We performed closed thoracic drainage surgery for the patient and treated his symptoms with etoricoxib(60 mg daily).Upon discharge,methotrexate was prescribed again.In subsequent follow-ups,there was no recurrence of joint and respiratory symptoms observed in the patient.CONCLUSION SAPHO syndrome has been proposed as a transitional stage between ankylosing spondylitis and psoriatic arthritis.One study reported a 0.29%incidence of spontaneous pneumothorax in patients with ankylosing spondylitis,higher than in the general population.Additionally,30%of patients with SAPHO syndrome test positive for HLA-B27,an antigen linked to ankylosing spondylitis.Symptomatically,some patients with SAPHO syndrome meet diagnostic criteria for ankylosing spondylitis,with sternoclavicular joint involvement and paravertebral ossific-ations resembling syndesmophytes in ankylosing spondylitis.These features suggest a possible linked between SAPHO syndrome and ankylosing spondylitis.
基金supported by the Start-Up Research Funding of Fujian Normal University(No.Y0720326K13)the National Natural Science Foundation of China(Nos.22103035 and 22033005)+2 种基金the National Key R&D Program of China(No.2022YFA1503900)Shenzhen Science and Technology Program(No.RCYX20231211090357078)Guangdong Provincial Key Laboratory of Catalysis(No.2020B121201002).
文摘Atomically precise palladium(Pd)clusters are emerging as versatile nanomaterials with applications in catalysis and biomedicine.This study explores the synthesis,structure evolution,and catalytic properties of Pd clusters stabilized by cyclohexanethiol(HSC_(6)H_(11))ligands.Using electrospray ionization mass spectrometry(ESI-MS)and single-crystal X-ray diffraction(SXRD),structures of the Pd clusters ranging from Pd4(SC_(6)H_(11))8 to Pd18(SC_(6)H_(11))36 were determined.This analysis revealed a structure evolution from polygonal to elliptical geometries of the PdnS2n frameworks as the cluster size increased.UV-Vis-NIR spectroscopy,combined with quantum chemical calculations,elucidated changes in the electronic structure of the clusters.Catalytic studies on the Sonogashira cross-coupling reactions demonstrated a size-dependent decline in activity attributed to variations in structural arrangements and electronic properties.Mechanistic insights proposed a distinctive Pd(Ⅱ)-Pd(Ⅳ)catalytic cycle.This research underscores how ligands and cluster size influence the structures and properties of Pd clusters,offering valuable insights for the future design and application of Pd clusters in advanced catalysis and beyond.
基金supported by the National Natural Science Foundation of China(Nos.22001006,22375002,22273057,22225401)the Anhui Provincial Natural Science Foundation(No.2308085Y10)+4 种基金the Open Project of Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Anhui University,Ministry of EducationThe National Key Research and Development Program of China(Nos.2022YFC_(2)403500,2020YFA0210800)The Universities Joint Laboratory of Guangdong,Hong Kong and Macao(No.130/07422011)the Natural Science Foundation of Guangdong Province(No.2022A1515011661)the China Postdoctoral Science Foundation(Nos.2023M730760,2023M740010)。
文摘Charge-transfer(CT)stoichiometric cocrystals are promising choice of organic materials for unveiling the structure-property relationship.However,due to the contradiction between large CT degree required for strong NIR absorption and flexible molecular stacking,construction of stoichiomorphism-based cocystals with near-infrared(NIR)photothermal property remains challenging.Herein,the first example of stoichiomorphism-based photothermal cocrystals were accomplished through the adaptive assembly of 3,3,5,5-tetramethylbenzidine(TMB)donor and 1,2,4,5-tetracyanobenzene(TCNB)acceptor.The selective cocrystallization could be controlled by varying the donor-acceptor stoichiometries via a surfactantassisted method,resulting in two cocrystals with 1:1(T1C1)and 1:2(T2C1)stoichiometries.The absorbance intensity of T1C1 at 808 nm was nearly twice that of T2C1,while the photothermal conversion efficiency(PCE)of the former was 60.3%±0.6%,approximately 80%of that for the latter(75.5%±2.6%),which might be caused by the different intermolecular interactions in distinct molecular stacking patterns.Notably,both excellent PCEs of stoichiometric cocrystals were attributed to the nonradiative transition process,including internal conversion and charge dissociation processes,as elucidated by femtosecond transient absorption spectroscopy measurements.Furthermore,T1C1 was used as an NIR heater for preparing agarose-based photothermal hydrogel,showing great potential for light-controlled in-situ gelation.This strategy of balancing the CT degree and molecular packing orientation not only uncovered the relationship between stoichiometric stacking and photothermal property,but also provided an opportunity to develop advanced organic optoelectronic materials.
文摘With the rapid development of human civilization,the concentration of CO_(2)in the atmosphere has sharply increased in the past century,resulting in global temperature anomaly,extreme climate events,and eco-environmental disturbances.The green-house gas CO_(2)is mainly released from the process of fossil fuel utilization and combustion.
基金financially supported by the National Natural Science Foundation of China(52202228,52402298)Science Research Project of Hebei Education Department(BJK2022011)+3 种基金Central Funds Guiding the Local Science and Technology Development of Hebei Province(236Z4404G)Beijing Tianjin Hebei Basic Research Cooperation Special Project(E2024202273)Science and Technology Correspondent Project of Tianjin(24YDTPJC00240)supported by the U.S.Department of Energy’s Office of Science,Office of Basic Energy Science,Materials Sciences and Engineering Division。
文摘The poor electrode/electrolyte interface compatibility and inferior electrolyte oxidative tolerance in commercial ethylene carbonate(EC)-based electrolytes have hindered the development of high-voltage sodium-ion batteries(SIBs).In this study,an anionic chemistry strategy is proposed to strengthen Na^(+)-anion coordination in the solvation sheath,and subsequently reduce the coordination numbers of EC solvents with the addition of NaClO_(4)into NaPF_(6)/EC/DEC electrolytes.Theoretical and experimental results confirm that the competitive coordination capabilities of Na^(+)-ClO_(4)^(-),with high binding energy,induce a wide electrochemical window up to 4.8 V,highly reversible Na^(+)plating/stripping,and fast desolvation kinetics at the electrode/electrolyte interface,thereby hindering the continuous electrolyte decomposition.The optimized electrolyte PEDCF-0.20 demonstrates weakened Na^(+)-EC coordination,increased interaction of Na^(+)-anion in solvation,facilitating the formation of an inorganic-rich interface layer.Consequently,a 2.1 A h cylindrical full cell of hard carbon//NaNi_(1/3)Fe_(1/3)Mn_(1/3)O_(2)delivers an impressive capacity retention of 93.7% after 300 cycles at an extended charging cutoff voltage of 4.1 V.This work provides a new insight into regulating the competitive coordination of anions to guarantee the remarkable cycling stability of high-voltage SIBs.
基金Prince Sultan University for their supportPrincess Nourah Bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R300)supported via funding from Prince Sattam Bin Abdulaziz University project number(PSAU/2025/R/1447).
文摘The fracture energy of fiber-reinforced concrete(FRC)affects the durability and structural performance of concrete elements.Advancements in experimental studies have yet to overcome the challenges of estimating fracture energy,as the process remains time-intensive and costly.Therefore,machine learning techniques have emerged as powerful alternatives.This study aims to investigate the performance of machine learning techniques to predict the fracture energy of FRC.For this purpose,500 data points,including 8 input parameters that affect the fracture energy of FRC,are collected fromthree-point bending tests and employed to train and evaluate themachine learning techniques.The findings showed that Gaussian process regression(GPR)outperforms all other models in terms of predictive accuracy,achieving the highest R2 of 0.93 and the lowest RMSE of 13.91 during holdout cross-validation.It is then followed by support vector regression(SVR)and extreme gradient boosting regression(XGBR),whereas K-nearest neighbours(KNN)and random forest regression(RFR)show the weakest predictions.The superiority of GPR is further reinforced in a 5-fold cross-validation,where it consistently delivers an average R2 above 0.96 and ranks highest in overall predictive performance.Empirical testing with additional sample sets validates GPR’s model on the key mix parameter’s impact on fracture energy,cementing its claim.The Fly-Ash cement exhibits the greatest fracture energy due to superior fiber-matrix interaction,whereas the glass fiber dominates energy absorption amongst the other types of fibers.In addition,increasing the water-to-cement(W/C)ratio from 0.30 to 0.50 yields a significant improvement in fracture energy,which aligns well with the machine learning predictions.Similarly,loading rate positively correlates with fracture energy,highlighting the strain-rate sensitivity of FRC.This work is the missing link to integrate experimental fracture mechanics and computational intelligence,optimally and reasonably predicting and refining the fracture energy of FRC.
基金Supported by Anhui Provincial Key Research and Development Plan,No.202104j07020048.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making precise treatment plans and improving patient prognosis.AIM To establish an intratumoral and peritumoral model for predicting ER in HCC patients following curative ablation.METHODS This study included a total of 288 patients from three Centers.The patients were divided into a primary cohort(n=222)and an external cohort(n=66).Radiomics and deep learning methods were combined for feature extraction,and models were constructed following a three-step feature selection process.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),while calibration curves and decision curve analysis(DCA)were used to assess calibration and clinical utility.Finally,Kaplan-Meier(K-M)analysis was used to stratify patients according to progression-free survival(PFS)and overall survival(OS).RESULTS The combined model,which utilizes the light gradient boosting machine learning algorithm and incorporates both intratumoral and peritumoral regions(5 mm and 10 mm),demonstrated the best predictive performance for ER following HCC ablation,achieving AUCs of 0.924 in the training set,0.899 in the internal validation set,and 0.839 in the external validation set.Calibration and DCA curves confirmed strong calibration and clinical utility,whereas K-M curves provided risk stratification for PFS and OS in HCC patients.CONCLUSION The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions.This model provides a noninvasive,effective,and reliable method for predicting ER after curative ablation of HCC.
基金National Medicinal Plants Board. Govt,of India,New Delhi,India for providing financial assistance in the form of Senior Research Fellowship to cam' out the present study
文摘Objective:To evaluate the antioxidant activity of aqueous extract of Atoringa oleifeta M.oleifera) young leaves by in vivo as well as in vitro assays.Methods:In vitro study included estimation of total phenolic,total ilavonol,total flavonoid and total antioxidant power(FRAP assay).Tn addition, in vivo study was done with the identified most effective dose of 200 nig/kg of its lyophilized powder on normal and diabetic rats.Its effect on different oxidative free radical scavenging enzymes,viz,superoxide dismutase(SOD),catalase(CAT),glutathione-S-transferase(GST),lipid peroxide(LPO) contents were measured.Results:Significant increase in activities of SOD.CAT, GST while,a decrease in LPO content was observed.Whereas,total phenolic,flavonoid and ilavonol contents in the extract were found to be 120 mg/g of CAK,40.5 mg/g of QEK and 12.12 mg/g of QE,respectively.On the other hand.FRAP assay results of M.oleifera leaves was(85.00±5.00)μM of Fe^+/g of extract powder.Conclusions:The significant antioxidant activities of M.oleifera leaves from both in vivo as well as in vitro studies suggests that the regular intake of its leaves through diet can protect normal as well as diabetic patients against oxidative damage.
文摘The design of an antenna requires a careful selection of its parameters to retain the desired performance.However,this task is time-consuming when the traditional approaches are employed,which represents a significant challenge.On the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended performance.In this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial antenna.The proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep network.This optimized network is used to retrieve the metamaterial bandwidth given a set of features.In addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.
基金funded by the Department of Science and Innovation/Mintek Nanotechnology Innovation Centre.
文摘Colorectal cancer(CRC)is among the leading causes of cancer mortality.The lifetime risk of developing CRC is about 5%in adult males and females.CRC is usually diagnosed at an advanced stage,and at this point therapy has a limited impact on cure rates and long-term survival.Novel and/or improved CRC therapeutic options are needed.The involvement of microRNAs(miRNAs)in cancer development has been reported,and their regulation in many oncogenic pathways suggests their potent tumor suppressor action.Although miRNAs provide a promising therapeutic approach for cancer,challenges such as biodegradation,specificity,stability and toxicity,impede their progression into clinical trials.Nanotechnology strategies offer diverse advantages for the use of miRNAs for CRC-targeted delivery and therapy.The merits of using nanocarriers for targeted delivery of miRNA-formulations are presented herein to highlight the role they can play in miRNA-based CRC therapy by targeting different stages of the disease.
基金This study was supported by the National Research Foundation of Korea(2017R1C1B1010627)the New and Renewable Energy Program of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant funded by the Korea Government Ministry of Trade,Industry and Energy(MTIE)(20163030013900,20183010013900)This study was supported by the Technology Development Program to solve climate changes of the National Research Foundation(NRF)funded by theMinistry of Science,ICT and Future Planning(NRF-2015M1A2A2057506,2019M1A2A2065614).
文摘Tandem device architectures offer a route to greatly increase the maximum possible power conversion efficiencies(PCEs)of polymer solar cells,however,the complexity of tandem cell device fabrication(such as selecting bandgaps of the front and back cells,current matching,thickness,and recombination layer optimization)often result in lower PCEs than are observed in single-junction devices.In this study,we analyze the influence of front cell and back cell bandgaps and use transfer matrix modeling to rationally design and optimize effective tandem solar cell structures before actual device fabrication.Our approach allows us to estimate tandem device parameters based on known absorption coefficients and open-circuit voltages of different active layer materials and design devices without wasting valuable time and materials.Using this approach,we have investigated a series of wide bandgap,high voltage photovoltaic polymers as front cells in tandem devices with PTB7-Th as a back cell.In this way,we have been able to demonstrate tandem devices with PCE of up to 12.8%with minimal consumption of valuable photoactive materials in tandem device optimization.This value represents one of the highest PCE values to date for fullerene-based tandem solar cells.
基金financially supported by the National Council for Scientific and Technological Development(CNPq,Brazil),Swedish-Brazilian Research and Innovation Centre(CISB),and Saab AB under Grant No.CNPq:200053/2022-1the National Council for Scientific and Technological Development(CNPq,Brazil)under Grants No.CNPq:312924/2017-8 and No.CNPq:314660/2020-8.
文摘Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R333)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.
基金supported by the National Key Research and Development Program of China(No.2016YFA0200301)the National Natural Science Foundation of China(Nos.21875211 and 51603181)。
文摘Encapsulation and controlled release of volatile molecules such as fragrances in a designed manner is important but challenging for the flavor and fragrance industry.Here,we report the tuning release of volatile molecules by postsynthetic modification of an amine-terminated metal-organic framework(MOF)MIL-101-NH_(2).By amidation,we obtained three MIL-101 MOFs,the trimethylacetamideterminated TC-MIL-101,the benzamide-terminated BC-MIL-101,and the oxalic acid monoamideterminated OC-MIL-101.All the MOFs can efficiently encapsulate volatile molecules.Moreover,we demonstrate that the release profile of volatiles can be widely tuned to sustain the release in several days to months and even over a year using different modified MIL-101 MOFs.We show that the release profiles are correlated with the binding energies between the vip volatiles and pores in MOFs.The pore diffusion and the synergistic transport are the rate-limiting step of the vip molecules from the modified MOFs.
基金Hallym University Research Fund,2019(HRF-201905-013).
文摘With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,which demands for new solutions.Terahertz(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information network.THz communication has great application prospects in military-civilian integration and coordinated development.In China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the world.Therefore,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G.This paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel model.Then,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver.Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.
基金This work was supported by the National Natural Science Foundation of China(62004058 and U21A2076)Natural Science Foundation of Hebei Province(F2020202022)+5 种基金State Key Laboratory of Reliability and Intelligence of Electrical Equipment(EERI_PI20200005)S&T Program of Hebei(215676146H and 225676163GH)Hebei Graduate Innovation Funding Project(CXZZBS2023037 and CXZZSS2023026)L.Ding thanks the National Key Research and Development Program of China(2022YFB3803300)the open research fund of Songshan Lake Materials Laboratory(2021SLABFK02)the National Natural Science Foundation of China(21961160720).
文摘Inverted perovskite solar cells(PSCs)have attracted interest due to their simple fabrication,long-term stability,and small hysteresis[1-3].It is noteworthy that the quality of the hole-transport layer(HTL)largely determines the device performance.Nickel oxide(NiO_(x))has been paid great attention as a hole-transport material in PSCs because of its natural p-type property,low cost,good stability,and high transmittance[4,5].
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2023R161)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR51).
文摘Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)applications.The SA is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock market.Various researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the SA for multiple languages,for instance,English and Chinese.Due to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted SA for Hindi movie reviews.The current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLSA-MR)model.The presented IMDLSA-MR technique initially applies different levels of pre-processing to convert the input data into a compatible format.Besides,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed data.The Deep Belief Network(DBN)model is utilized to analyse and classify the sentiments.Finally,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the work.Different experimental analyses were conducted to validate the better performance of the proposed IMDLSA-MR model.The comparative study outcomes highlighted the enhanced performance of the proposed IMDLSA-MR model over recent DL models with a maximum accuracy of 98.92%.
文摘The main objective of this study is to understand the runoff, sediment yield and water quality of the Upper Indus River Basin of Pakistan. To achieve this goal, specific objectives have been met which include, setup of a hydrological model using Soil and Water Assessment Tool (SWAT) then calibration and validation of the hydrological model using river discharges and in the end investigating the performance of the hydrological model by SWAT. This research will have great impacts on socio-economic conditions of Pakistan because study of upper Indus River basin is imperative to provide data needed for its management, and to warrant that it is sustainable to support the increasing population and conservational flows. A set of programmable mapping components MapWindow Geographic Information System (GIS) was used which is an open source GIS based mapping application. It is SWAT used spatially distributed information on elevation, land use, slope and soil. The program Sequential Uncertainty Fitting ver.2 (SUFI-2) in a combination of uncertainty analysis and calibration of outputs was used in SWAT-CUP. SWAT model used input data, which have climate information to obtain results. The observed climate data of temperature gauges and rain gauge were used as input in the SWAT model;the calibration results for three discharge stations were produced. The initial P-factor value was satisfactory but more iteration to attempt narrow uncertainty band with improving goal function, resulted in small percentage of observed data within uncertainty band. A warm up period of three years (1979-1982) was used for simulation of SWAT model. The model was calibrated for selected three catchments for the period 1982-2000 and validated for period 2001-2010. Results are quite comparable with the observed flows.
基金This study was funded by the Shanghai Science and Technology Committee and Shanghai Hutchison Pharmaceuticals Company.
文摘Background:The Shexiang Baoxin Pill(MUSKARDIA)has been used for treating coronary artery disease(CAD)and angina for more than 30 years in China.Nevertheless,methodologically sound trials on the use of MUSKARDIA in CAD patients are scarce.The aim of the study is to determine the effects of MUSKARDIA as an add-on to optimal medical therapy(OMT)in patients with stable CAD.Methods:A total of 2674 participants with stable CAD from 97 hospitals in China were randomized 1:1 to a MUSKARDIA or placebo group for 24 months.Both groups received OMT according to local tertiary hospital protocols.The primary outcome was the occurrence of a major adverse cardiovascular event(MACE),defined as a composite of cardiovascular death,non-fatal myocardial infarction(MI),or non-fatal stroke.Secondary outcomes included all-cause mortality,non-fatal MI,non-fatal stroke,hospitalization for unstable angina or heart failure,peripheral revascularization,angina stability and angina frequency.Results:In all,99.7%of the patients were treated with aspirin and 93.0%with statin.After 2 years of treatment,the occurrence of MACEs was reduced by 26.9%in the MUSKARDIA group(MUSKARDIA:1.9%vs.placebo:2.6%;odds ratio=0.80;95%confidence interval:0.45-1.07;P=0.2869).Angina frequency was significantly reduced in the MUSKARDIA group at 18 months(P=0.0362).Other secondary endpoints were similar between the two groups.The rates of adverse events were also similar between the two groups(MUSKARDIA:17.7%vs.placebo:17.4%,P=0.8785).Conclusions:As an add-on to OMT,MUSKARDIA is safe and significantly reduces angina frequency in patients with stable CAD.Moreover,the use of MUSKARDIA is associated with a trend toward reduced MACEs in patients with stable CAD.The results suggest that MUSKARDIA can be used to manage patients with CAD.Trial registration:chictr.org.cn,No.ChiCTR-TRC-12003513.
基金the grants from the Health and Family Planning Commission of Hunan Province (No.B2015-106)the Natural Science Foundation of Hunan Province of China (No.2018JJ6012).
文摘To the Editor:Primary familial brain calcification (PFBC) is a rare genetically degenerative disease that is generally characterized by symmetrical,bilateral calcinosis in the basal ganglia,thalamus,dentate nuclei,and other brain regions and mainly manifests with neurological and psychiatric symptoms. A growing number of studies have reported associations between this condition and pathogenic mutations,such as those in the SLC2OA2,PDGFRB,PDGFB,XPR1,and MYORG genes, Few studies have evaluated familial clinical characteristics, such as the volume of basal ganglia calcification (VBGC), and the results of clinical tests to determine serum levels of calcium (Ca),magnesium (Mg),phosphorus (P),iron (Fe), aluminum (A1),arsenic (As),cobalt (Co),parathyroid hormone (PTH),and calcitonin (Ct),or the relationship between patient age and the VBGC in PFBC.
